Overview
Publication in the field of technical sciences
Includes supplementary material: sn.pub/extras
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Table of contents (8 chapters)
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Front Matter
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Back Matter
Keywords
About this book
Andreas Bihlmaier describes a novel method to model dynamic spatial relations by machine learning techniques. The method is applied to the task of representing the tacit knowledge of a trained camera assistant in minimally-invasive surgery. The model is then used for intraoperative control of a robot that autonomously positions the endoscope. Furthermore, a modular robotics platform is described, which forms the basis for this knowledge-based assistance system. Promising results from a complex phantom study are presented.
Authors and Affiliations
About the author
Andreas Bihlmaier is leader of the Cognitive Medical Technologies group in the Institute for Anthropomatics and Robotics – Intelligent Process Control and Robotics Lab (IAR-IPR) at the Karlsruhe Institute of Technology (KIT). His research focuses on cognitive surgical robotics for minimally-invasive surgery, as part of the SFB/Transregio 125 “Cognition-Guided Surgery”.
Bibliographic Information
Book Title: Learning Dynamic Spatial Relations
Book Subtitle: The Case of a Knowledge-based Endoscopic Camera Guidance Robot
Authors: Andreas Bihlmaier
DOI: https://doi.org/10.1007/978-3-658-14914-7
Publisher: Springer Vieweg Wiesbaden
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Fachmedien Wiesbaden 2016
Softcover ISBN: 978-3-658-14913-0Published: 18 August 2016
eBook ISBN: 978-3-658-14914-7Published: 12 August 2016
Edition Number: 1
Number of Pages: XV, 267
Number of Illustrations: 120 b/w illustrations
Topics: Artificial Intelligence, Minimally Invasive Surgery, Pattern Recognition